Where Growth Companies are Funded and Traded Across Borders

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Ideal for investors. As for me, I just like transparency. ;) P.S. Couldn't track down the founders (both have facebook accounts but no twitter, what the?!), but I would be curious to know how funderbeam compares to Angellist.
@v4violetta @bramk AL and CrunchBase are among our data sources. But we're aiming at providing deeper startup intelligence for investors, media, consultants, researchers, and other entrepreneurs. Which, as Bram rightly points out, places us in more direct competition with Mattermark, as well as DataFox, CB Insights, etc. You can also check out a few other competitors that our algorithm has mapped on the Funderbeam profile at (no signup or subscription needed for this profile)
Hi guys. We've just raised €500k and thought you might like to know where we're going with our data-intelligence platform. Automated creation of (startup) investment syndicates, liquidity to investors by enabling an aftermarket, plus a whole lot less bureaucratic friction in the process. And blockchain tech making sure it's all secure. Here's the announcement itself:
This looks quant driven rather than consumer driven.
@douglascrets Yeah, I was thinking...
@v4violetta interestingly the reaction to it suggests something should be offered in the non investing space about this.
@douglascrets which reaction do you mean? :)
Looks like a basic Crunchbase with website traffic info which probably isn't so accurate...
@laurent_sabbah CB (and indeed AL) are both among our data partners. Other current data sources include LinkedIn and SimilarWeb, as well as Funderbeam users themselves, who suggest profile edits and fixes. But our current data-intelligence product goes quite a bit farther than CB, which you mentioned. Here are a few examples: - a lot of API-pulled data is dirty + has gaps. We try to address both. First, we've built algorithms to improve startup categorization on two fronts. One, we use the Industry Classification Benchmark that leading stock exchanges employ - helps investors who want to compare public and private companies using similar classification. Two, we've whittled 20k+ company tags down to 45 tag clusters that are essentially our new industry sectors. - The above categorization effort is really helpful in mapping competitors properly + in benchmarking companies against others in the same space. That's one feature both investors and startup folks like, as it helps discover competition + then track and/or analyze it. - Follow function (startup + investor tracking). We track various events and updates affecting both companies and investors. From funding to team changes, etc. See it here: Also, we'll soon launch email notifications for companies you track. - Predictive analysis, i.e. estimates based on algorithms & models we've built. This helps fill some of the data gaps in early-stage companies with intelligent guesses. This includes the estimated quarter of their next funding round, their valuation, development stage, and funding probability (% likelihood of them raising money in the next round if they go for it, based on an analysis of available structural characteristics at thousands of other startups.) - It also bears mentioning that Funderbeam defines startups as younger than 7 years of age. We also place some other limits to ensure that a company with 10k employees doesn't show up on an early-stage angel's radar when they do a search at In other words, we'll rather keep our database smaller, but cleaner and more relevant to the early-stage ecosystem. You're right in that Alexa, SimilarWeb and others estimate web traffic - and their estimates do miss the mark quite a bit sometimes. Just take it with a pinch of salt -- as you should with any sort of triangulation.
@villuarak Thank you for the extremely detailed answer :) I'll definitely pay more attention to it now and the next time I look up a startup I'll give funderbeam a chance!
@laurent_sabbah My pleasure. Don't expect Funderbeam to get it right, though. That's an impossible standard to meet. Instead, I think of it as a percentage game. Especially in a space where there's a lot of fog, tightly-held folders, and buckets full of data that looks like it can quack, but upon closer inspection turns out to be a rubber ducky with an old dry booger on its beak. :)